Comparison of clustering methods for identification of outdoor measurements in pollution monitoring

Xu Yang, Lingxi Zhu, Sio Lam, Laurie Cuthbert, Yapeng Wang

研究成果: Conference article同行評審

1 引文 斯高帕斯(Scopus)

摘要

This paper considers the problem of post-processing air pollution data to clearly identify outdoor clusters, by removing indoor data and "noise" caused by air from indoors mingling with air from outdoors. In this paper, several different clustering algorithms are compared using data from measurements in Macao. It is shown that X-means generally outperforms the others for this purpose and can successfully separate data modified by noise. Such a technique simplifies the collection of large data sets since the person taking the measurements does not have to make any advance decisions about what is pure outdoor, or pure indoor, data. However, it is also shown in this work that setting up suitable procedures can be quite complex.

原文English
文章編號012014
期刊IOP Conference Series: Earth and Environmental Science
257
發行號1
DOIs
出版狀態Published - 10 5月 2019
事件2019 9th International Conference on Future Environment and Energy, ICFEE 2019 - Osaka, Japan
持續時間: 9 1月 201911 1月 2019

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